activity
20202022
most citedPrompting for a conversation: How to control a dialog model?

5 citations · 6 across the 5 of their papers we have counts for

collaborators

8 papers

cs.CL2022

The Architectural Bottleneck Principle

Tiago Pimentel, Josef Valvoda, Niklas Stoehr +1

In this paper, we seek to measure how much information a component in a neural network could extract from the representations fed into it. Our work stands in contrast to prior prob…

cs.CL20225 cited

Prompting for a conversation: How to control a dialog model?

Josef Valvoda, Yimai Fang, David Vandyke

Dialog modelling faces a difficult trade-off. Models are trained on a large amount of text, yet their responses need to be limited to a desired scope and style of a dialog agent. B…

cs.CL20211 cited

A Word on Machine Ethics: A Response to Jiang et al. (2021)

Zeerak Talat, Hagen Blix, Josef Valvoda +3

Ethics is one of the longest standing intellectual endeavors of humanity. In recent years, the fields of AI and NLP have attempted to wrangle with how learning systems that interac…

cs.CY2021

What About the Precedent: An Information-Theoretic Analysis of Common Law

Josef Valvoda, Tiago Pimentel, Niklas Stoehr +2

In common law, the outcome of a new case is determined mostly by precedent cases, rather than by existing statutes. However, how exactly does the precedent influence the outcome of…

cs.CL2020

Analyzing Neural Discourse Coherence Models

Youmna Farag, Josef Valvoda, Helen Yannakoudakis +1

In this work, we systematically investigate how well current models of coherence can capture aspects of text implicated in discourse organisation. We devise two datasets of various…

cs.CL2020

SIGMORPHON 2020 Shared Task 0: Typologically Diverse Morphological Inflection

Ekaterina Vylomova, Jennifer White, Elizabeth Salesky +25

A broad goal in natural language processing (NLP) is to develop a system that has the capacity to process any natural language. Most systems, however, are developed using data from…